원문정보
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초록
영어
Controlling UAV requires high-precision dynamic information input. However, mini UAV needs more demands because of the its small volume. Using MEMS sensor can make the UAV become high-precision, low power consumption and inexpensive machine. In this research, the core part is focusing on STM32F405, designing and implement the attitude and heading reference system (AHRS) based on 3-axis MEMS gyroscope, 3-axis MEMS accelerometer and magnetometer. Quaternion Kalman filter has been adopted in this study in order to achieve the attitude measurement and error control of transporter.
목차
Abstract
1. Introduction
2. System Architecture
2.1. Hardware Architecture of AHRS
2.2. Coordinate Frame and Attitude Angle Estimation
3. Attitude Calculation
3.1 Initial Value of the Quaternions
3.2. Direction Transformation Matrix
3.3. Update Attitude Based on Quaternion Differential Equations
3.4. Runge Kutta Algorithms
4. Kalman Filter Algorithms
4.1. State Equation
4.2. Observations Update Equation :
4.3. Kalman Filter Iteration
5. Simulation and Analysis
6. Conclusion
Acknowledgements
References
1. Introduction
2. System Architecture
2.1. Hardware Architecture of AHRS
2.2. Coordinate Frame and Attitude Angle Estimation
3. Attitude Calculation
3.1 Initial Value of the Quaternions
3.2. Direction Transformation Matrix
3.3. Update Attitude Based on Quaternion Differential Equations
3.4. Runge Kutta Algorithms
4. Kalman Filter Algorithms
4.1. State Equation
4.2. Observations Update Equation :
4.3. Kalman Filter Iteration
5. Simulation and Analysis
6. Conclusion
Acknowledgements
References
저자정보
참고문헌
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